HENDRICKX ET AL.: TEXTURE, SOIL MOISTURE, AND INFILTRATION DATA 1515

of the Des Moines lobe was very clean and nearlydevoid of what we now call New Ulm till.

Boundary Location from Texture, Soil Moisture, and Infiltration Data1

J. M. H. HENDRICKX, P. J. WIERENGA, M. S. NASH, AND D. R. NIELSENZ

ABSTRACTThe objective was to ascertain how well different soil physical

properties or parameters could be used to identify boundary loca-tions along a soil transect. A transect was established with 91 po-sitions, 1 m apart. The infiltration rate was measured along thetransect with small (0.3-m diam) and large (1.0-m diam) infiltrationrings. Thereafter, 91 soil samples were taken at a depth of 0.3 mfor texture analysis. Also, 91 neutron access tubes and tensiometerswere installed in two parallel lines 0.3 m apart. Soil-water contentwas measured 16 times at the 0.3-m depth before and after floodingthe transect. Soil-water tension was measured 13 times after flood-ing. The moving split window technique was used as a numericalprocedure for boundary location. Boundaries detected—based on soiltexture, water content, and water tension data—nearly coincided.Under dry conditions, one set of water content measurements re-sulted in almost the same boundaries as detected with soil texturedata. Under moist conditions, several sets of measurements wereneeded to detect boundaries. Boundary detection with infiltrationdata was less satisfactory. Window width had little effect on detec-tion of boundaries. The moving split window technique appears tobe a useful tool for establishing boundaries along transects, basedon water content and tension data, or in combination with soil tex-ture data.

'Journal article 1192, Agricultural Experiment Station, NewMexico State Univ., Las Cruces, NM 88003. Received 23 Sept. 1985.

1 Soil Physicist, Netherlands Soil Survey Institute, P. O. Box 98,6700 AB Wageningen, The Netherlands, (formerly Research As-sistant, New Mexico State Univ.); Professor, Graduate Student, andVisiting Professor, Dep. of Crop and Soil Sciences, New MexicoState Univ., Las Cruces, NM 88003.

Additional Index Words: spatial variability, soil-water content,soil-water tension, soil survey, soil classification.

Hendrickx, J.M.H., P.J. Wierenga, M.S. Nash, and D.R. Nielsen.1986. Boundary location from texture, soil moisture, and infiltra-tion data. Soil Sci. Soc. Am. J. 50:1515-1520.

LOCATION OF BOUNDARIES between different soiltypes is traditionally based on qualitative eval-

uation of soil morphological characteristics with em-phasis on texture. Because texture strongly effects soilmoisture properties (Taylor and Ashcroft, 1972), tex-tural characteristics are often used for evaluation ofsoil-water parameters (Brakensiek et al., 1981; Mc-Cuen et al., 1981; Rawls and Brakensiek, 1982) or landclassification for irrigation (Thompson et al., 1981).As a result, boundaries based on texture also becomeboundaries for soil moisture properties. Although thispractice seems to yield adequate results, few quanti-tative evaluations have been made. However, in 1973,Webster (1978) applied a numerical procedure forquantitative boundary location, called the moving splitwindow technique. Boundaries located with the mov-ing split window technique (Webster, 1973, 1978)showed good agreement with boundaries located qual-itatively in the field. Therefore, this method allowsone to locate and compare boundaries based on dif-ferent variables in an objective manner.

The purpose of this study was to determine the po-tential of soil-water content, soil-water tension, and

1516 SOIL SCI. SOC. AM. J., VOL. 50, 1986

70

£~ 60

5 50

o<-> 40o

1 30oI 20

10

50

16 31 46 61POSITION NUMBER

76 91

Fig. 1. Clay and sand content along transect at depth 0.3 m.

infiltration rate measurements for boundary locationwith the moving split window technique.

MATERIALS AND METHODSThe experiment was conducted at the Plant Science Re-

search Center of New Mexico State Univ. 14-km southwestof Las Cruces, N.M. Soil at the experimental site is a Glen-dale clay loam (fine loamy, mixed calcareous, thermic TypicTorrifluvents) with the water table at approximately 3 m.The soil consists of approximately 0.7 m of silty clay loamoverlaying fine-to-medium sands. Climate at the experimen-tal site is characterized by an abundance of sunshine, lowrelative humidity, and an average Class A pan evaporationof 2.39 m yr~'. Rainfall is extremely variable. Average an-nual precipitation is 0.23 m with 52% of the rainfall occur-ring between July 1 and September 30. Average maximumtemperature is highest in June at 36 °C, and lowest in Jan-uary at 13°C.

The experiment was conducted in 1982 on a laser-leveledplot 92-m long and 4-m wide, surrounded by borders. Atransect was located in this plot, consisting of 91 positions1 m apart. Infiltration rate was measured at each positionwith double-ring infiltrometers. The inner ring had a di-ameter of 0.3 m and the outer ring a diameter of 1 m. Theentire plot was kept flooded during infiltration measure-ments. Five double-ring infiltrometers were pushed about0.05 m into the flooded soil. Rate of fall of the water levelinside inner and outer rings was measured with an electricsensor over a period of about 1 h. Following these mea-surements, infiltration rate was measured at the next fivepositions along the transect. Upon completion of the infil-tronieter measurements, access tubes were placed at all po-sitions, exactly, in the center of each inner infiltration ring.While placing access tubes soil samples were taken from the0.3-m depth for texture analysis. At a distance of 0.3 m fromeach access tube, on a line parallel to the transect with neu-tron access tubes, 91 tensiometers were installed with theirtip at the 0.3-m depth. Fifty of the 91 tensiometers wereinstalled in dry soil before irrigation. They were filled withwater and left to equilibrate with dry soil. One week later(June 7), soil-water tension was measured with a pressuretransducer for field tensiometers (Soil Measurement Sys-tems, Las Cruces, NM) as described in Marthaler et al. (1983),and soil-water content at the 0.3-m depth was measured witha neutron probe. After these measurements, the plot wasflooded and the remaining 41 tensiometers were installed.On June 10, the plot was flooded again for 1 d. BetweenJune 11 and August 5, during which time water redistributedwithin the soil profile, water content and soil-water tensionwere measured on 13 different days.

Soil samples were analyzed for very coarse, coarse, me-dium, fine, and very fine sand by dry sieving, and for clay,

ATEXTURE

16 46 61 76 91

100

50

5i

WATER CONTENT

16 31 46 61 76 91

100 -

16 76 9131 46 61POSITION NUMBER

Fig. 2. Partition of transect based on soil texture, water content, andwater tension with window width of 24 positions.

by the pipette method (Day, 1965). Silt content was deter-mined by difference.

With the moving split window technique, two adjacentsections of the transect, each consisting of n positions, arecompared using the Hotelling-Lawley trace. This method isa direct analogue of the univariate Student's / statistic (Mor-rison, 1967). Where the value of the Hotelling-Lawley trace,or its F value, reaches a maximum is considered the optimalboundary location. To enable use of a narrow window, orto reduce computer time when many variables at each po-sition are considered, the original data set can be reducedwith a principal component technique (Webster, 1973).Principal components of texture data were calculated withthe PRINCOMP procedure of SAS (Ray, 1982). The firstthree principal components used in the moving split windowtechnique accounted for 82% of the variation present in thetexture data. The F value of the Hotelling-Lawley trace wascalculated with the GLM procedure as SAS (Ray, 1982).

RESULTS AND DISCUSSIONPercentages of clay and sand (Fig. 1) along the tran-

sect manifest considerable variation with distancealong the transect. Figure 2 presents results using themoving split window technique. Figure 2a shows Fvalues for soil texture as a function of position alongthe transect (window width is 24). Peaks found at po-sitions 31, 54, and 70 partition the transect into foursegments, each with a different texture: segment A fromposition 1 to 31, segment B from position 32 to 54,segment C from position 55 to 70, and segment Dfrom position 71 to 91. Figure 1 shows that the clayfraction decreases suddenly after position 31, and in-creases again slightly after position 54. Segments Cand D do not differ in clay percentage, nor do seg-ments A and C differ in silt percentage. However, allfour segments have different sand percentages. Exceptfor clay and silt percentages of segment B, coefficientsof variation for clay, silt, and sand are lower for in-dividual segments than for the entire transect (Hen-drickx, 1984).

HENDRICKX ET AL.: TEXTURE, SOIL MOISTURE, AND INFILTRATION DATA 1517

0.40 r

> 0.36

z 0.32

8 0.28

< 0.24

Table 1. Means, standard deviations, and coefficients ofvariation of the water content (vol. %) of the

soil along the transect.

^uo35 r

13 26 39 52 65 78 91

o<n•

i26 39 52 65

POSITION NUMBER

Fig. 3. Soil-water content and soil-water tension along transect atdepth 0.3 m on 23 July 1982.

Partitioning of the transect on the basis of texturedata was compared with that on the basis of soil mois-ture data. Figure 3 presents soil-water contents andsoil-water tensions along the transect on July 23 in amoist soil. Soil moisture shows considerable variationalong the transect. To decrease the number of varia-bles at each point, the 16 d of soil-water content andthe 13d of soil-water tension measurements were re-duced with principal component analysis to threeprincipal components. These principal components arelinear combinations of the original soil-water contentand soil-water tension variables. The first principalcomponent accounts for as much as possible of thevariation in the data; the second principal componentaccounts for as much as possible of the variation left(Chatfield and Collins, 1980). The first three principalcomponents of water content data accounted for 87%of the variation in the data, and the first three prin-cipal components of water tension for 86%. Using thethree principal components, boundaries were deter-mined by the moving split window technique as be-fore, again with a window width of 24 positions (Fig.2b and 2c). The peaks in the plots of F value vs. po-sition number for water content and tension almostconcide with peaks found by analysis of texture data.

Peaks for water content data (Fig. 2b) partition thetransect into four segments, each with a different watercontent regime: segment A from position 1 to 32, seg-ment B from position 33 to 50, segment C from po-sition 51 to 75, and segment D from position 76 to91. On the basis of the analysis with a window widthof 24 positions, segment A should be taken from po-sition 13 to 32 and segment D from position 76 to 79,because one does not know whether a peak occursbetween positions 1 to 12 and positions 80 to 91.However, below we will show, with a window widthof eight positions, identical peaks are found. In ad-

Date

7 June 198211 June 198230 July 1982

7 June 198211 June 198230 July 1982

7 June 198211 June 198230 July 1982

7 June 198211 June 198230 June 1982

7 June 198211 June 198230 July 1981

N

919191

323232

181818

252525

161616

StandardMean deviation

Entire transect24.736.230.2

Segment A27.035.331.3

Segment B16.536.829.0Segment C25.437.030.8

Segment D28.035.828.4

5.01.42.0

2.91.31.3

2.41.02.0

3.51.41.7

1.40.81.7

Coefficientof variation

20.23.96.7

10.73.74.2

14.72.76.9

13.73.85.6

5.02.16.1

dition, Hendrickx (1984) presents for each measure-ment day the coefficients of variation for soil-watercontent and soil-water tension found in segments Athrough D. Because the coefficients of variation of seg-ments A and D are not higher than in segments B andC, it is justified to include the first and last positionsin partitioning of the transect. To show soil-water con-tent differences between segments, average water con-tent and its standard deviation for each segment andfor the entire transect on June 7 (relatively dry soil),June 11 (relatively wet soil), and July 30 (relativelymoist soil), are presented in Table 1. Note that watercontent differences increase when the soil becomesdrier. Hendrickx (1984) presents the data of the othermeasurement days.

Peaks for soil-water tension (Fig. 2c) partition thetransect into four segments, each with a different soil-water tension regime: segment A from position 1 to25, segment B from position 26 to 50, segment C fromposition 51 to 72, and segment D from position 73 to91. The peak at position 63 was neglected because itis located within a one-half window width (12 posi-tions) of the peak at position 73. Experience has shownthe moving split window technique detects meaning-ful peaks when these are at least a one-half windowwidth apart. To show soil-water tension differencesbetween segments, average soil-water tension and itsstandard deviation for each segment and for the entiretransect on June 11 (wet soil) and July 30 (moist soil)are presented in Table 2. Note again that differencesin soil-water tension increase when the soil becomesdrier. Hendrickx (1984) presents the data for the othermeasurement days.

The -F-value peaks shown in Fig. 2 are highly sig-nificant, indicating the partition of the transect intofour segments is meaningful. Weak peaks found inanalysis of texture data are amplified three- to fourfoldin the analysis of both water content and water tensiondata (Fig. 2a vs. Fig. 2b, 2c). Although peaks do not

1518 SOIL SCI. SOC. AM. J., VOL. 50, 1986

25

20

10

E 5

§25

15

10

SMALL INFILTROMETER

13 26 39 52 65 78 91

LARGE INFILTROMETER

13 78 9126 39 52 65POSITION NUMBER

Fig. 4. Infiltration rates along transect measured with large (diam1.0 m) and small (diam 0.3 m) infiltrometer.

50

[ -A A..A

0.3m RINGS

16 31 46 61 76 91_i

50 BI.Om RINGS

I 16 76 9131 46 61POSITION NUMBER

Fig. 5. Partition of transect based on infiltration rates measured withsmall and large infiltrometers.

occur at exactly the same positions, the general trendis that the transect is partitioned by texture, water con-tent, and water tension in the same manner. Soil-watercontent gives the sharpest boundaries, which indicatesits potential to divide large areas into similar domains.

Figure 4 presents infiltration rates along the tran-sect, and Fig. 5 presents results of application of themoving split window technique to infiltration rate data.Data of the small infiltrometer rings show peaks atpositions 23, 38, 53, and 77; data of the large infiltro-meter rings show peaks at positions 25, 38, 54, and75. Instead of one peak at position 31 (texture), 32,(water content), or 25 (tension), infiltration data showtwo peaks: one around position 24 and one at position38. This discrepancy may be due to the fact that in-filtration rates were measured at the soil surface,whereas other data were obtained at 0.3-m depth.Three of the four boundaries detected with infiltrationrate data are near boundaries located on the basis ofeither texture, water content, or soil-water tension.

Effect of Number of MeasurementsSoil texture does not change over time and one set

of measurements should provide an adequate descrip-

Table 2. Means, standard deviations, and coefficients ofvariation of the tension (kPa) of the soil

along the transect.

Date

11 June 198230 July 1982

11 June 198230 July 1982

11 June 198230 July 1982

11 June 198230 July 1982

11 June 198230 July 1982

N

8691

2525

2525

2222

1419

StandardMean deviation

Entire transect6.4

19.7Segment A

7.620.6

Segment B6.5

15.3Segment C

5.316.7

Segment D6.0

28.1

1.47.6

0.72.6

0.82.9

1.13.4

1.911.7

Coefficientof variation

2238

1013

1219

2121

3242

tion along the transect. Assuming no major effects ofinitial water content, and no effects of water qualityon final infiltration rates, one set of measurements ofthe infiltration rate should suffice. By contrast, soilmoisture status changes constantly and more than oneset of measurements may be needed over a given pe-riod for an adequate description of the soil moistureregime. The moving split window technique was ap-plied to a single set of measurements taken during wet,moist, and dry soil conditions to determine how manysets of measurements were needed to detect a soilboundary. Results for soil-water content and soil-watertension are presented in Fig. 6 and 7, respectively.Peaks found with the water content data (Fig. 6a), whenthe soil was dry, agree well with peaks shown in Fig.2b, based on an analysis of all water content data.However, peaks observed immediately after floodingdo not agree with any peaks detected before (Fig. 6b),or disappear completely (Fig. 6c). Therefore, it followsthat under wet conditions, the transect has a ratherhomogeneous soil-water content (see also Table 1).Peaks start to appear again (Fig. 6d) in a moist soil,after 6 weeks of draining and drying, and coincidereasonably well with peaks shown in Fig. 2b and Fig.6a. Peaks detected with the soil-water tension data ina wet and moist soil (Fig. 7) do not agree well withpeaks shown in Fig. 2c. This poor agreement may becaused by the nonlinear relation between soil-watercontent and soil-water tension. In addition, the coef-ficient of variation of soil-water tension (Table 2) isat least three times higher than the coefficient of var-iation of soil-water content (Table 1), which makespeak detection more difficult.

It appears that one set of water content measure-ments in a dry soil is as good an indicator as all setsof water content measurements combined. This maybe caused by inclusion of the June 7 data from a drysoil. Use of all combined measurements of soil-watertension (Fig. 2c) was superior to that for only one set,in either a wet or a moist soil (Fig. 7).

The main-reason that results obtained with themoving split window technique are better for dry soil-water contents, as compared to wet soil-water content,is that water content in wet soils differs less among

HENDRICKX ET AL.: TEXTURE, SOIL MOISTURE, AND INFILTRATION DATA 1519

150

IOO

50

UJ

350

JUNE 7, 1982MEAN WATER CONTENT = 0,247 m3 m~3

A16 31 46 61 76 91

MEAN WATER CONTENT = 0.362 m3 mJUNE 11, 1982

.3™-3

16 31 46 61 76 91

MEAN WATER CONTENT = 0.325 m mJUNE 14, 1982

3 "3

16 31 46 61 76 91

50 - MEAN WATER CONTENT = 0.302 m mJULY 30, 1982

3 ~3

IS 31 46 61POSITION NUMBER

76 91

Fig. 6. Partition of transect based on four sets of water content mea-surements with window width of 24 positions.

different soils than water content in dryer soils. Wos-ten et al. (1986) present data for 22 standard soils fromThe Netherlands that show the above-mentioned be-havior. At saturation, the range of volumetric watercontents among 22 soils was 24.9 volume %. At soil-water tensions of 3, 10, 50, 250, and 1600 kPa therange was 33.0, 44.4, 43.8, 37.8, and 30.3 volume %,respectively. These data indicate drier soils with a soil-water content around field capacity have the largestpotential for soil boundary detection, because a widerange is evidence of large differences between soils.

Effect of Window WidthThe window width of 24 positions used in the anal-

ysis was somewhat arbitrary. Therefore, all calcula-tions were repeated for window widths of 8, 16, and32 positions to check the effect of window width onpeak location. The number of positions that any ofthe three peaks was shifted left or right was noted, andcompared with peaks found using a window width of32 positions (Table 3). The window width had littleeffect on location of boundaries when all sets of mea-surements of soil-water content or soil-water tensionwere considered. When one set of measurements wasconsidered, water content measurements taken in adry soil adequately identified peaks. If the soil was wetor moist, location of the boundaries became sensitiveto window width (Table 3) and peaks became lower(Fig. 6 and 7). Boundaries determined with infiltrationrates were most sensitive to window width.

Figure 8 shows all peaks obtained with an analysisof all water content data, using window widths of 8,16, 24, and 32 positions. Changes occurring in peakswith increasing window width are typical for all var-iables analyzed. A wide window exhibits fewer andlarger peaks and a smoother graph. Because samplingalong a transect at short regular intervals violates the

50

JUNE 14, 1982MEAN WATER TENSION = 9.6 kPa

I 16 31 46 61 76 91

JULY 30, 1982MEAN WATER TENSION = 19.7 kPa

50

I 16 31 46 61 76 91POSITION NUMBER

Fig. 7. Partition of transect based on two sets of water tension mea-surements with window width of 24 positions.

50

50

WINDOW WIDTH = 8 POSITIONS

I6 31 46 61 76 91

WINDOW WIDTH = 16 POSITIONS

I"IOO

50

IOO

50

16 31 46 61

IWINDOW WIDTH = 24 POSITIONS

76 91

c

I 16 31 46 61 76 91

DWINDOW WIDTH = 32 POSITIONS

16 31 46 61POSITION NUMBER

76 91

Fig. 8. Partition of transect based on all water content measurementsusing four window widths.

basic statistical assumption of independent and ran-dom samples, application of statistical tests for deter-mination of significant peaks will not always yield re-liable results. For example, we cannot test whether thesmall peak at position 40 in Fig. 8b is significant. Al-

Table 3. Largest shift in peak position with decreasingwindow width for several variables measured

along the transect.Window width

Variable 32 24 16

All texture dataAll water content dataAll water tension dataMean water content = 24.7 m3 m~3

Mean water content = 30.2 m3 m'3Mean water content = 36.2 m3 m'3

Mean water tension = 19.7 kPaMean water tension = 9.6 kPaInfiltration rate (small ring)Infiltration rate (large ring)

0000000000

0000131233

0010131255

0011131354

1520 SOIL SCI. SOC. AM. J., VOL. 50, 1986

though the moving split window technique uses a nu-merical procedure, interpretation of peaks—especiallysmall peaks—remains somewhat subjective. Becausepartitioning of the transect into homogeneous seg-ments was our goal, only large, clear peaks found witha large window width were recognized in this study.For other studies, use of a narrow window width andsubsequent inspection of the many smaller peaks maybe more appropriate.

The scale of this study was small and results seemof more importance for experimental plot differentia-tion and spatial variability applications within a fieldthan for large scale soil survey and soil series differ-entiation. However, another study by Wierenga et al.(1986) showed along a 3-km transect in the Chihua-huan desert of southern New Mexico that soil bound-aries determined on the basis of soil-water contentobservations coincided with boundaries indepen-dently determined with a soil survey.

Results from this study indicate the moving splitwindow technique is a useful tool for numerically es-tablishing boundaries along transects. The techniqueis especially useful for boundary location, based onwater content data of soils at fields capacity. This im-plies that for an initial survey for boundary locations,water content data rather than texture data could beused.

ACKNOWLEDGMENTDuring the writing phase of the study the senior author

was supported by the Agricultural Engineering Departmentof Texas A&M Univ. and the Texas Agricultural ExperimentStation (grant no. H-6441).

Soil-geomorphic Evolution of a Boroll Catena in Southwestern Alberta1

D. J. PENNOCK AND W. J. VREEKEN2

ABSTRACTThe geomorphic and pedological processes that have influenced

the development of a Boroll catena in south-western Alberta areexamined using a combination of sedimentological and pedologicaltechniques. Four geomorphic episodes are responsible for the sedi-ments in the catena: the deposition of glacial till, two colluvial ep-isodes, and a final eolian episode that deposited a thin mantle ofsediment over the landscape. The vertical and lateral distribution ofgrain size fractions in the landscape is largely the result of thesegeomorphic processes. The vertical distributions of Fe and CaCO,show some relict features from earlier phases of pedogenesis, whereasthe organic C values appear to be related only to the present con-figuration of the landscape.

Additional Index Words: Holocene, soil parent material, sedi-mentology.

Pennock, D.J., and W.J. Vreeken. 1986. Soil-geomorphic evolutionof a Boroll Catena in southwestern Alberta. Soil Sci. Soc. Am. J.50:1520-1526.

1 Contribution from the Dep. of Geography, Queen's Univ.,Kingston, ON, Canada. Received 24 Feb. 1986.2 Assistant Professor, Dep. of Geography, Scarborough College,Univ. of Toronto, 1265 Military Trail, Scarborough, ON, Canada,MIC 1A4; and Professor, Dep. of Geography, Queen's Univ.,Kingston, ON, Canada.

IN MILNE'S FORMULATION of the catena concept(1936), he attributes the observed differences be-

tween soils along a catena to the action and interactionof geomorphic, pedological, and hydrplogical or drain-age processes. Moreover, he recognized that the in-tensity of these processes or the processes themselvesmay have varied through time, yielding a historicalcontext for catenary studies. Despite Milne's multiple-process definition of a catena, subsequent researchershave primarily focused on the influence of individualenvironmental variables, notably drainage, on catenadevelopment. Although this fragmentation of the ca-tena concept is more in accordance with Jenny's (1941)state factor approach to soil genesis, the initial, inte-grated catena definition is lost.

In this paper we examine the geomorphic, drainage,and pedological process that have influenced a catenaof Udic Boroll soils developed in glacial till in sou^h-ern Alberta. Studies on adjacent surfaces to the catenaindicated that considerable colluvial and eolian activ-ity had occurred since deglaciation (Pennock, 1984).Since the thick, soil-strategraphical columns used toestablish the sequence of events were not present onthe till surface, an alternative research design was de-